| PINS静基座对准中的理论与算法的研究 |
| |
| 引用本文： | 刘准,陈哲.PINS静基座对准中的理论与算法的研究[J].北京航空航天大学学报,2002,28(6):617-620. |
| |
| 作者姓名： | 刘准 陈哲 |
| |
| 作者单位： | 北京航空航天大学,自动化科学与电气工程学院 |
| |
| 摘 要： | 分析了平台式惯导系统(PINS)静基座条件下的可观测性,采用系统可观测矩阵的条件数来定量计算PINS静基座可观测性能,找出该条件下的可观测矩阵条件数最小的3个不可观测变量.采用了自适应Kalman算法和常规Kalman算法对简化模型进行了仿真比较.仿真结果表明前者比后者滤波收敛快.进而提出了一种基于Elman神经网络的快速对准方法.
|
| 关 键 词： | 惯性导航 可观测性 神经网络 姿态角误差 |
| 文章编号： | 1001-5965(2002)06-0617-04 |
| 收稿时间： | 2001-04-05 |
| 修稿时间： | 2001年4月5日 |
Study on Theory and Arithmetic of Stationary Alignment for PINS |
| |
| LIU Zhun,CHEN Zhe.Study on Theory and Arithmetic of Stationary Alignment for PINS[J].Journal of Beijing University of Aeronautics and Astronautics,2002,28(6):617-620. |
| |
| Authors: | LIU Zhun CHEN Zhe |
| |
| Institution: | Beijing University of Aeronautics and Astronautics, School of Automation Science and Electrical Engineering |
| |
| Abstract: | The observability of stationary alignment for PINS was analyzed systemically, and condition number of observable matrix was adopted to compute quantificationally the observability of stationary alignment for PINS. Three unobservable states with the least condition mumber were chosen in this condition, then both adaptive Kalman filter and general Kalman filter was employed to compare for simplified model. Simulation results showed the former was faster than later. Furthermore, a alignment method based on Elman neural network was proposed. |
| |
| Keywords: | inertial navigation observability neural networks attitude errors |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《北京航空航天大学学报》浏览原始摘要信息 |
| 点击此处可从《北京航空航天大学学报》下载免费的PDF全文 |
